Purpose: The purpose of this study is to evaluate the effectiveness of oral positioning stent, the BinkieRTTM in radiation treatment for head and neck cancer patients in terms of tongue positions reproducibility, tongue doses and material properties. Materials and Methods: 24 cases using BinkieRTTM during radiation treatments were enrolled. The tongue was contoured on planning CT and CBCT images taken every 3 days during treatment, and then the DSC and center of tongue shift values were analyzed to evaluate the reproducibility of the tongue. The tongue dose was compared in terms of dose distribution when using BinkieRTTM and different type of oral stents (mouthpiece, paraffin wax). Randomly selected respective 10 patients were measured tongue doses of initial treatment plan for nasal cavity and unilateral parotid cancer. Finally, In terms of material evaluation, HU and relative electron density were identified in RTPS. Results: As a result of DSC analysis, it was 0.8 ± 0.07, skewness -0.8, kurtosis 0.61, and 95% CI was 0.79~0.82. To analyze the deviation of the central tongue shift during the treatment period, a 95% confidence interval for shift in the LR, SI, and AP directions were indicated, and a one-sample t-test for 0, which is an ideal value in the deviation(n=144). As a result of the t-test, the mean and SD in the LR and SI directions were 0.01 ± 0.14 cm (p→.05), 0.03 ± 0.25 cm (p→.05), and -0.08 ± 0.25 cm (p ←.05) in the AP direction. In the case of unilateral parotid cancer patients, the Dmean to the tongue of patients using BinkieRTTM was 16.92% ± 3.58% compared to the prescribed dose, and 23.99% ± 10.86% of patients with Paraffin Wax, indicating that the tongue dose was relatively lower when using BinkieRTTM (p←.05). On the other hand, among nasal cavity cancer patients, the Dmean of tongue dose for patients who used BinkieRTTM was 4.4% ± 5.6%, and for those who used mouthpiece, 5.9% ± 6.8%, but it was not statistically significant (p→.05). The relative electron density of Paraffin Wax, BinkieRTTM and Putty is 0.94, 0.99, 1.26 and the mass density is 0.95, 0.99 and 1.32 (g/cc), Transmission Factor is 0.99, 0.98, 0.96 respectively. Conclusion: The result of the tongue DSC analysis over the treatment period was about 0.8 and Deviation of the center of tongue shifts were within 0.2 cm, the reproducibility was more likely excellent. In the case of unilateral head and neck cancer patients, it was found that the use of BinkieRTTM rather than Paraffin Wax or Putty can reduce the unnecessary dose irradiated to the tongue. This study might be useful to understand of BinkieRTTM's properties and advantages. And also it could be another considered option as oral stent to keep the reproducibility of tongue and reducing dose during head and neck radiation treatments.
From January 2020 to October 2021, more than 500,000 academic studies related to COVID-19 (Coronavirus-2, a fatal respiratory syndrome) have been published. The rapid increase in the number of papers related to COVID-19 is putting time and technical constraints on healthcare professionals and policy makers to quickly find important research. Therefore, in this study, we propose a method of extracting useful information from text data of extensive literature using LDA and Word2vec algorithm. Papers related to keywords to be searched were extracted from papers related to COVID-19, and detailed topics were identified. The data used the CORD-19 data set on Kaggle, a free academic resource prepared by major research groups and the White House to respond to the COVID-19 pandemic, updated weekly. The research methods are divided into two main categories. First, 41,062 articles were collected through data filtering and pre-processing of the abstracts of 47,110 academic papers including full text. For this purpose, the number of publications related to COVID-19 by year was analyzed through exploratory data analysis using a Python program, and the top 10 journals under active research were identified. LDA and Word2vec algorithm were used to derive research topics related to COVID-19, and after analyzing related words, similarity was measured. Second, papers containing 'vaccine' and 'treatment' were extracted from among the topics derived from all papers, and a total of 4,555 papers related to 'vaccine' and 5,971 papers related to 'treatment' were extracted. did For each collected paper, detailed topics were analyzed using LDA and Word2vec algorithms, and a clustering method through PCA dimension reduction was applied to visualize groups of papers with similar themes using the t-SNE algorithm. A noteworthy point from the results of this study is that the topics that were not derived from the topics derived for all papers being researched in relation to COVID-19 (